By default, ZenML uses the data flowing between steps of your pipeline to determine the order in which steps get executed. The following example shows a pipeline in which step_3 depends on the outputs of step_1 and step_2. This means that ZenML can execute both step_1 and step_2 in parallel but needs to wait until both are finished before step_3 can be started. 
from zenml.pipelines import pipeline

@pipeline
def example_pipeline(step_1, step_2, step_3):
    step_1_output = step_1()
    step_2_output = step_2()
    step_3(step_1_output, step_2_output)
If you have additional constraints on the order in which steps get executed, you can specify non-data dependencies by calling step.after(some_other_step): 
from zenml.pipelines import pipeline

@pipeline
def example_pipeline(step_1, step_2, step_3):
    step_1.after(step_2)
    step_1_output = step_1()
    step_2_output = step_2()
    step_3(step_1_output, step_2_output)
This pipeline is similar to the one explained above, but this time ZenML will make sure to only start step_1 after step_2 has finished.